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:: Volume 5, Number 17 (quarterly journal of Fiscal and Economic Policies 2017) ::
3 2017, 5(17): 97-115 Back to browse issues page
Assessment of Stock Price Predictions Using Artificial Neural Network (ANN)
Abstract:   (193 Views)
The stock market agents should increase their prediction accuracy to maximize their returns, and it needs some advanced tools. In this article stock price of 50 companies in the Tehran Stock Exchange have been modeled using feedforward artificial neural networks. In this way, the daily stock prices are used from December 1384 to December 1394. The predictions accuracy are evaluated with four statistical indicators. The results show that accuracy of ANN predictions is very high. In some cases, although the prediction accuracy is higher, the correctness is lower. Therefore, in the assessment of the prediction, evaluation of the correctness has a significant contribution
Keywords: Neural Networks, Prediction, Stock Return, Tehran Stock Exchange
Full-Text [PDF 957 kb]   (125 Downloads)    
Type of Study: Research | Subject: Special
Received: 2017/08/2 | Accepted: 2017/08/2 | Published: 2017/08/2
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Assessment of Stock Price Predictions Using Artificial Neural Network (ANN) . 3. 2017; 5 (17) :97-115
URL: http://qjfep.ir/article-1-692-en.html
Volume 5, Number 17 (quarterly journal of Fiscal and Economic Policies 2017) Back to browse issues page
فصلنامه سیاستهای مالی و اقتصادی Quarterly Journal of Fiscal and Economic Policies
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